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How did this argument work when talking about locally run LLMs?

by andybak 3y ago

moffkalast 3y ago
[flagged]
- deleted 3y ago
  [deleted]
shinycode 3y ago
I think what he meant by AI is AI in services everywhere. I attended an AWS summit this week and 9 out of 10 of the almost 100 companies had AI written on the punchline of their stand. This is the AI the author meant, AI integrated into services that collect data and use that data to feed the AI to sell more stuff.
- nyc_data_geek 3y ago
  I was at a VC conference several months ago and ever since I've joked that if I learned nothing else while I was there, I learned how to spell "AI". It's the frothiest space now. Interest rates are high, everyone wants thay next funding round, hence they glom onto the buzz and hype even if they don't have a product or a valid use case, even if they don't solve for anything.
- kjkjadksj 3y ago
  If anything thats a signal of where not to invest. Ai is a tool but not always the best tool, sometimes (most of the time potentially) simple linear regression or t test/wilcox will do. All done in a line of code in the standard library of R at least.
sbierwagen 3y ago
He would probably argue that future LLMs are less likely to have their weights released. It is remarkable and strange that we have so many open-weights models right now, considering how much they cost to make.
- deleted 3y ago
  [deleted]
- AnthonyMouse 3y ago
  It costs a lot of money to an individual, not to a corporation. Estimates are that it cost Facebook around $20 million for LLaMA, for example. This is less than 0.1% of their annual revenue. It's slightly weird that some of the companies doing this are VC-backed startups with no obvious business model, but that's hardly the only way to create them. Companies like Facebook could continue to release them purely for the PR. The cost is within the range of what could be done from donations by a non-profit organization. It's the sort of thing you might build a business model around in the same way that IBM or Intel does with Linux -- an obvious candidate here would be models released by Nvidia/AMD/Intel/Apple/etc. You might also build a business model out of consulting services rather than hardware sales, e.g. here's a free LLM and now you can pay us to integrate it with your company's systems. This is also assuming that nobody ever figures out how to train a model using distributed computing. The second that happens there will be arbitrarily many free models because there are a zillion people willing to contribute a day's worth of consumer GPU time to a free model project.
  - rustcleaner 3y ago
    >It's slightly weird that some of the companies doing this are VC-backed startups with no obvious business model, but that's hardly the only way to create them. If you are a multi hundred-millionaire, do you privately train a model for fun to release for bragging rights and possibly expose yourself directly to some eyewateringly stupid high statutory damage liability? Or do you get a few friends together, funnel your fun money into a protective vehicle that can be sued instead of you, and go to town having fun and maybe making something of it?

How did this argument work when talking about locally run LLMs?

moffkalast 3y ago

[flagged]

deleted 3y ago
[deleted]

shinycode 3y ago

I think what he meant by AI is AI in services everywhere. I attended an AWS summit this week and 9 out of 10 of the almost 100 companies had AI written on the punchline of their stand. This is the AI the author meant, AI integrated into services that collect data and use that data to feed the AI to sell more stuff.

nyc_data_geek 3y ago
I was at a VC conference several months ago and ever since I've joked that if I learned nothing else while I was there, I learned how to spell "AI". It's the frothiest space now. Interest rates are high, everyone wants thay next funding round, hence they glom onto the buzz and hype even if they don't have a product or a valid use case, even if they don't solve for anything.
kjkjadksj 3y ago
If anything thats a signal of where not to invest. Ai is a tool but not always the best tool, sometimes (most of the time potentially) simple linear regression or t test/wilcox will do. All done in a line of code in the standard library of R at least.

sbierwagen 3y ago

He would probably argue that future LLMs are less likely to have their weights released. It is remarkable and strange that we have so many open-weights models right now, considering how much they cost to make.

deleted 3y ago
[deleted]
AnthonyMouse 3y ago
It costs a lot of money to an individual, not to a corporation. Estimates are that it cost Facebook around $20 million for LLaMA, for example. This is less than 0.1% of their annual revenue. It's slightly weird that some of the companies doing this are VC-backed startups with no obvious business model, but that's hardly the only way to create them. Companies like Facebook could continue to release them purely for the PR. The cost is within the range of what could be done from donations by a non-profit organization. It's the sort of thing you might build a business model around in the same way that IBM or Intel does with Linux -- an obvious candidate here would be models released by Nvidia/AMD/Intel/Apple/etc. You might also build a business model out of consulting services rather than hardware sales, e.g. here's a free LLM and now you can pay us to integrate it with your company's systems. This is also assuming that nobody ever figures out how to train a model using distributed computing. The second that happens there will be arbitrarily many free models because there are a zillion people willing to contribute a day's worth of consumer GPU time to a free model project.
- rustcleaner 3y ago
  >It's slightly weird that some of the companies doing this are VC-backed startups with no obvious business model, but that's hardly the only way to create them. If you are a multi hundred-millionaire, do you privately train a model for fun to release for bragging rights and possibly expose yourself directly to some eyewateringly stupid high statutory damage liability? Or do you get a few friends together, funnel your fun money into a protective vehicle that can be sued instead of you, and go to town having fun and maybe making something of it?